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Dynamic Production Scheduling for a Process Industry

Author

Listed:
  • Renato de Matta

    (University of Iowa, Iowa City, Iowa)

  • Monique Guignard

    (University of Pennsylvania, Philadelphia, Pennsylvania)

Abstract

Capacity-oriented production scheduling can be described as the assignment of competing products to several single level, capacitated production lines over a given planning horizon. This study was initially motivated by the production planning of various types of tiles by a tile manufacturing company. We considered different integer programming formulations and found that a disaggregated model, while increasing the size of the model, lends itself best to Lagrangian techniques and produces the strongest bounds. Additionally, from every Lagrangian solution, we can generate a feasible production schedule by systematically reassigning lines from products whose production exceeded demand to products with unsatisfied demands. The technique is not specific to tile companies, but can be used by any firm where product setups on production lines can be scheduled between consecutive periods with changeover cost, but without production loss. Our computational experience with real data from the tile company and randomly generated problem instances gave excellent lower and upper bounds.

Suggested Citation

  • Renato de Matta & Monique Guignard, 1994. "Dynamic Production Scheduling for a Process Industry," Operations Research, INFORMS, vol. 42(3), pages 492-503, June.
  • Handle: RePEc:inm:oropre:v:42:y:1994:i:3:p:492-503
    DOI: 10.1287/opre.42.3.492
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    Citations

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    Cited by:

    1. Raf Jans, 2009. "Solving Lot-Sizing Problems on Parallel Identical Machines Using Symmetry-Breaking Constraints," INFORMS Journal on Computing, INFORMS, vol. 21(1), pages 123-136, February.
    2. Karina Copil & Martin Wörbelauer & Herbert Meyr & Horst Tempelmeier, 2017. "Simultaneous lotsizing and scheduling problems: a classification and review of models," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 1-64, January.
    3. Ozdamar, Linet & Birbil, Sevket Ilker, 1998. "Hybrid heuristics for the capacitated lot sizing and loading problem with setup times and overtime decisions," European Journal of Operational Research, Elsevier, vol. 110(3), pages 525-547, November.
    4. Fiorotto, Diego Jacinto & Jans, Raf & Alexandre de Araujo, Silvio, 2018. "Process flexibility and the chaining principle in lot sizing problems," International Journal of Production Economics, Elsevier, vol. 204(C), pages 244-263.
    5. Rapine, Christophe & Penz, Bernard & Gicquel, Céline & Akbalik, Ayse, 2018. "Capacity acquisition for the single-item lot sizing problem under energy constraints," Omega, Elsevier, vol. 81(C), pages 112-122.
    6. Diego Fiorotto & Silvio Araujo, 2014. "Reformulation and a Lagrangian heuristic for lot sizing problem on parallel machines," Annals of Operations Research, Springer, vol. 217(1), pages 213-231, June.
    7. Jans, Raf & Degraeve, Zeger, 2007. "Meta-heuristics for dynamic lot sizing: A review and comparison of solution approaches," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1855-1875, March.
    8. Tao Wu & Zhe Liang & Canrong Zhang, 2018. "Analytics Branching and Selection for the Capacitated Multi-Item Lot Sizing Problem with Nonidentical Machines," INFORMS Journal on Computing, INFORMS, vol. 30(2), pages 236-258, May.
    9. Monique Guignard, 2007. "En hommage à Joseph-Louis Lagrange et à Pierre Huard," Annals of Operations Research, Springer, vol. 149(1), pages 103-116, February.

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